Plugging Holes In Machine Learning

The number of companies using machine learning is accelerating, but so far there are no tools to validate, verify and debug these systems. That presents a problem for the chipmakers and systems companies that increasingly rely on machine learning to optimize their technology because, at least for now, it creates the potential for errors that are extremely difficult to trace and fix. At the same time, it opens up new opportunities for companies that have been developing static tools to expand their reach well beyond just the chip, where profits are being squeezed by system vendors. But as shown in part one of this series, that will take years rather than months to fix. Research is just beginning on how to tackle these problems, let alone develop comprehensive tool suites. “Across…